[gmx-users] dynamic cross correlation map (DCCM)
tsjerkw at gmail.com
Tue Jan 19 13:23:30 CET 2010
Well I'd say that 'DCCM' refers to the matrix (map) of correlations
and not to that of covariances. More specifically, it refers to
correlations of positional fluctuations. PCA, on the other hand,
refers to the extraction of components or axes which better describe
the data than the original axes do, not specifying what kind of data,
nor whether correlations or covariances be used for their
determination. That's quite a distinction.
g_covar gives the covariance matrix, not the correlation matrix. I
believe there was a modified version in the contributions section
which was able to compute correlations.
On Tue, Jan 19, 2010 at 12:50 PM, Justin A. Lemkul <jalemkul at vt.edu> wrote:
> leila karami wrote:
>> I want to obtain dynamic cross correlation map (DCCM). I used following
>> command for obtaining covariance matrix.
>> g_covar -f traj.xtc -s topol.tpr -o eigenval.xvg -v eigenvec.trr -l
>> covar.log -xpm covar.xpm.
>> my system consists protein of 70 aminoacids. I want survey correlated and
>> anti-correlated motion between residues.
>> Is my manner true? If so, which of output files in above give me dynamic
>> cross correlation map (DCCM)? otherwise, please guide me.
> No one has ever been able to explain to me the difference between DCCM and
> PCA, so I'd say you're correct at least in obtaining the covariance matrix,
> which will give you information about correlated and anticorrelated motion.
> "DCCM" seems to be a popular term with the AMBER crowd, but I don't know
> that their manual even gives the equations used for such an analysis to
> potentially differentiate it from PCA. I believe there are some tips in
> their mail reflector, however.
> Justin A. Lemkul
> Ph.D. Candidate
> ICTAS Doctoral Scholar
> MILES-IGERT Trainee
> Department of Biochemistry
> Virginia Tech
> Blacksburg, VA
> jalemkul[at]vt.edu | (540) 231-9080
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Tsjerk A. Wassenaar, Ph.D.
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